Comment by kypro
6 hours ago
Room where? You're obviously not going to hire someone for their knowledge alone in late 2026... ChatGPT probably knows more than you know in every domain. What questions could I ask you that ChatGPT wouldn't be able to answer?
ChatGPT is a fantastic encyclopedia for knowledge retrieval and even is occasionally accurate!
It doesn't yet know when I brushed my teeth last, what specific foods in what quantities give me heartburn/indigestion, what that funky smell from my running shoes might be.
It can write pretty good code on a recursive loop when its provided a clear target. It can write better code when it has someone who understand architecture guiding it. It can review code reasonably well as well.
ChatGPT tied to robotics might even be able to do more interesting things!
It does pretty poor on highly specific knowledge where a RAG better supports -- something like Agent Search at GCP or AI Search at Cloudflare. But it can synthesize.
In effect, we've built an amazing library registry and need to up our librarian skills and the skills of people or systems that can use the information the librarian and their system can find.
The point of the knowledge is that it helps you ask the right questions, not so much the ability to answer them.
Knowledge has been available just by asking Google for decades now. The LLM makes it easier but it's a difference of degree not of kind
Until the models are 100% reliable knowledge will be required in order to quickly spot issues and work efficiently with the model to address them.
The room comes from recognizing that, in many many domains, you don't even know the questions to ask.
Beautifully said.
I do wonder though about the optimizations within it, what could be the most optimal way to achieve such room (ie. knowing which questions to ask)
Yes, learning and tinkering is still really the greatest way to achieve that
but I think what I am talking about can be better simplified with the analogy of a gym: previously what used to be necessary (manual work/labour) but when most people got into information work, even then there was/is a need for it (physical work), then we saw the evolution of machines specifically designed to optimize for it and we got machines specifically designed for this training, which helped push people's body to their absolute limits.
I do wonder if an hyper-optimized environment of learning and for asking questions (or more so knowing the know how on which questions to ask), this whole process might be optimized for it and what that process might would look like is a source of curiosity to me.
A relevant video which talks about similar topics: Bodybuilding for the mind: https://www.youtube.com/watch?v=o0DtxUJ6rAc
You won’t hire someone to answer questions for you; you might hire someone to make decisions for you. And domain expertise is still very useful in both making good decisions and convincing other people to trust your decisions
Know what to ask is about as important as the answer. You can't do that very well without domain knowledge.
I'm not sure how it plays out in 5 or 10 years, but that's how it is now.
Maybe people will be hired for the question they can actually ask and not for the raw knowledge they have